Context-Aware Labels: Generation and Verifcation Seng W. Loke Department of Computer Science and Computer Engineering, L Trobe Universit, Australia Email: s.loke@latrobe.edu.au Abstact-ystems to date have labels which are assigned by a person, e.g., tagging an object or a place with a keyword or phrase. Given some entities already labelled, a formal mecha nism of generating labels using spatial context (detectable by sensors) is useful, not only t create new labellings without manual efort, but also that the labels can be used as queries to verify spatial properties of collections of objects. I. INTRODUCTION There ae numerous applications for labelling the world ranging fom tourist guides, memory aids, advertising, warn ings to helping the blind [5]. What of the world do we label? The three ontological categories of people, things and places seem a reasonable answer, and labelling associates a label or tag to people, things or places, in order to describe aspects of the entity's contents, properties, and identify (uniquely) the entity within a space of other entities. Most systems to date have labels which are assigned by a person, e.g., mobile geo-tagging a note, object with GPS coordinates, or tagging a place with a keyword or phrase, such as [3], [2]. ' Our view is that, given some entities already labelled, meaningful labels can not only be provided by a person but tat certain types of labels and compositions of labels can be inferred or generated based on common spatial relationships among labelled entities, that is, the labels are generated using context information of the entities being labelled. We require that there is a formally described language for labels and that these spatial relationships can be detectable via sensors (with some data processing). Roughly speaking, we aim towards a label generation system 2 I which takes detectable spatial relationships or context information among entities and an initial set of labellings of entities, and yields new labels, Le. I: spatial contextsxinitial labellings - new labellings 1 A long list of spatial annotation projects is at http:/www.elasticspace.comJ2004/06/spatial-annotation; http:/layar.eu provides augmented reality style viewing of labels of the world; similar to Layar is the Sekai Camera http:/vator.tv/news!show/2009-02-19-time-to start-tagging-the-physical-world 2 0ur use of the word "system" here refers to formal system as opposed to a sofware system. 978-1-4244-5328-3/10/$26.00 ©201O IEEE 776 We contend that new meaningful labellings can be generated automatically by exploiting the spatial context information about the entities. II. A CONTEXT-AwARE LABEL GENERATION SYSTEM This section gives an example of a formal system I for generating context-awae labels, comprising four ingredi ents: • labels l, which ae syntactically well-formed labels given in EBNF. One could invent a domain-specifc set of labels. But a example of a small generic label language is as follows: L ::=EI L $L I collection (L) I collection.e• I pcollection (L) I pcollection.e• I container (0) I container.e• I near L I lin I [inside lin ::= in Q I lin < in Q Iinside ::= inside 0 I [inside < inside 0 E::=PI Q I 0 where E denotes a string, which is a label for an entity, and can either be a label for a person P, a place Q, or an object 0 (thing), and E denotes the joining of two alternative labels for an entity (Le., an object, people or place), Le., SI E S2 is comparable to two labels given to the same entity (simila to two diferent tags for a video on youtube). The other labels are derived fom the relative spatial relationships between the entities, as we detail below. • entities e, which are in three ontological categories, people, places and things, to which tags or labels are associated. • labellings p:e:l, where an entity e is labelled l given by an agent p (person or sofware), or more generally, A - p:e:l expressing that e has label l assigned by p if assumptions A holds. Note that we might leave out p in discussions, when it is not important to take that into account or it is obvious fom context; when the labelling is not by a person but by a system generating the label, we may use s instead. We denote the labelling